Prevalence in Iceland
tests <- fread("Sheet1.csv")
positives <- fread("Sheet2.csv")
dat <- merge(tests,positives,by="V1",suffixes=c("_tests","_pos"))
dat[,V1:=as.Date(paste0(dat$V1,".2020"),format="%d.%m.%Y")]
setkey(dat,"V1")
NA_to_null(dat)
dat[,':='(cumdeCodeTests=cumsum(`deCODE genetics_tests`),
cumdeCodePos =cumsum(`deCODE genetics_pos`),
cumNUHITests =cumsum(`NUHI*_tests`),
cumNUHIPos =cumsum(`NUHI*_pos`))]
dat <- cbind(dat,dat[,binconf(cumdeCodePos,cumdeCodeTests)])
Pop <- 360000 ## Icelandic population
plot_ly(data=dat, y = ~PointEst, x=~ V1, type="scatter", mode="line",
line=list(color="orange"), name="Estimated Prevalence") %>%
add_trace(y= ~Lower, line=list(dash='dash'), name="Lower 95%-CI") %>%
add_trace(y=~Upper, line=list(dash='dash'), name="Upper 95%-CI") %>%
add_trace(y= ~cumNUHIPos/Pop,line=list(color="navy"), name="Tested Positive") %>%
layout(xaxis=list(title="Date"),yaxis=list(title="Share of Population"))